"PREDICTION OF DIABETES USING MACHINE LEARNING."

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Authors: Kamal Acharya
Cited by: 0

Abstract

"Today, the modern way of life for people leads their eating habits more than ever towardsfast-foods and already-to-use items. Diabetes is one of the most lethal diseases in the World.It is additionally an inventor of various varieties of disorders for example: coronary failure,blindness, urinary organ diseases etc. In such cases each individual needs to be diagnosedwith diabetes periodically by different blood tests. Such studies add considerable sums ofexpense to a large number of individuals and require facilities and time. It is possible to usemachine learning algorithms as computer aided systems to predict if a person is highlyprobable to have diabetes or not, in order to reduce huge number of people who require totake diagnosis blood tests, to save time and money.This paper focuses on developingpredictable model using various machine learning methods such as Decision Tree, LogisticRegression, na\u00efve bayes algorithm and Random Forests for predicting incident diabetes usingmedical records."

Fields of Study & Subjects

Artificial Intelligence in Healthcare Data Mining and Machine Learning Applications Natural Antidiabetic Agents Studies

Publication details

Journal / source
IEEE DataPort
Publication date
12 February 2026
Language
EN
Document type
Dataset